Apparatus and Method for Producing A Flow Profile

ABSTRACT

A method for generating a flow profile of an inhalation device is described. The method comprises the step of measuring acoustic emissions induced by inhalation flow through the inhalation device. The method further comprises the step of detecting peak frequencies in the measured acoustic emissions and generating a flow profile based on the detected peak frequencies. A corresponding device is also described.

The invention relates to an apparatus and a method for producing a flowprofile. In particular, the invention relates to an apparatus and methodfor producing a flow profile of an inhalation device, such as aninhaler.

BACKGROUND

Inhaler devices are used in the medical industry to administer drugs asa powder or using an aerosol, for example. The effectiveness of the drugadministration may be dependent on how the device is used, which may berelated to a flow rate or flow profile that is achieved by a user of theinhaler. Accordingly, it is desirable to measure an inspiratory flowrate as a function of time (i.e., a flow profile) for a patient using aninhaler device. Such a measurement can be used, for example, to supportclinical trials to assess the breathing style of the participants of thetrails, and for measuring the usage of the inhaler device during trialsto assist in evaluating device usage effectiveness. The measurements mayalso be used to train users in how to use the inhaler according to aninhalatory profile in accordance with effective usage of the device,during supervised or unsupervised training, for example. The inhalationmeasurement may produce assessments and corrective suggestions for theuser. Moreover, adherence monitoring could also be achieved by producinga flow profile, since it is potentially useful to use inhalatory flowmeasurements as part of a system used by medical practitioners that wishto evaluate adherence to a course of treatment.

It is known to estimate flow rate by measuring the audio power presentin a selected frequency band in the audio spectrum. The power measuredin this selected frequency band is then converted to a flow rate using apreviously determined calibration table, which includes values ofmeasured audio power within a filtered bandwidth and known flow rates.

To use this known method successfully, there are a number of factors tocontrol, such as the propagation path for the signal from an inhalerdevice, for example, to a microphone, and the gain and the sensitivityof the microphone and associated soundcard may also vary. Together thesefactors can limit the accuracy of the final flow rate estimate. Tomitigate these variable factors, the microphone may typically be a highquality repeatable device, which is attached to the inhaler to reducethe variations in propagation path and coupling.

Generally, it is desirable to make the flow measurements with as littledisturbance to the user as possible and with a minimum amount ofmodification/additional apparatus. Accordingly, there is a desire toimprove this method of obtaining a flow rate or flow profile from aninhaler device.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure can be understood with reference to thedescription of the embodiments set out below, in conjunction with theappended drawings in which:

FIG. 1 is a graph illustrating a relationship between spectral peak of aswirl tone of an inhaler device and air flow rate through the inhalerdevice;

FIG. 2 is a graph of acoustic power versus flow rate of four inhalersused to obtain spectral peak frequencies;

FIG. 3 shows a mobile device according to an aspect of the invention;

FIG. 4 illustrates the mobile device schematically;

FIG. 5 illustrates a calibration curve of audio power against flow ratefor an inhaler device;

FIG. 6 illustrates a graph of measured data from a microphone (uppergraph) and a spectrogram generated from the measure data (lower graph);

FIG. 7 graphically illustrates a method shown in a flow chart of FIG. 8;

FIG. 8 is a flow chart depicting a method performed by a processor ofthe mobile device; and

FIG. 9 illustrates a series of graphs used to illustrate the methodshown in the flow chart of FIG. 8 when performed using a smartphone anda general purpose computer.

DESCRIPTION

According to a first aspect of the invention there is provided a methodfor generating a flow profile of an inhalation device, comprising thesteps of: measuring acoustic emissions induced by inhalation flowthrough the inhalation device; detecting two or more peak frequencies inthe measured acoustic emissions; and generating a flow profile based onthe detected peak frequencies. Therefore, it is possible to moreaccurately determine a flow profile for an inhalation device during usethat is broadly independent on the relative proximity of the inhalationdevice and a measuring device (e.g., microphone).

Each of the peak frequencies may represent a spectral peak of an airflow, which may be describe as a rotating or a rotational air flow,through the inhalation device at a predetermined flow rate.

The acoustic emissions may be measured over a predetermined period oftime and the two or more peak frequencies are detected at regularintervals over the predetermined period of time.

The flow profile may be generated using a predetermined relationshipbetween the two or more peak frequencies and respective flow ratesthrough the inhalation device, and the predetermined relationship may berepresented by a look-up table.

The method may further comprise detecting acoustic power of the measuredacoustic emissions and generating the flow profile based on the detectedacoustic power and the detected peak frequencies.

According to a second aspect of the invention there is provided a methodfor generating a flow profile of an inhalation device, comprising thesteps of: measuring acoustic emissions induced by inhalation flowthrough the inhalation device; detecting one or more peak frequencies inthe measured acoustic emissions; detecting acoustic power of themeasured acoustic emissions; and generating a flow profile based on thedetected acoustic power and the detected peak frequencies. Therefore, itis possible to more accurately determine a flow profile based on ameasured audio power for an inhalation device during use that is broadlyindependent on the relative proximity of the inhalation device and ameasuring device (e.g., microphone).

Each of the peak frequencies may represent a spectral peak of an airflow, which may be describe as a rotating or a rotational air flow,through the inhalation device at a predetermined flow rate.

The acoustic emissions may be measured over a predetermined period oftime and the one or more peak frequencies and the acoustic power aredetected at regular intervals over the predetermined period of time.

The flow profile may be generated using predetermined relationshipsbetween the one or more peak frequencies and respective flow ratesthrough the inhalation device, and acoustic power and respective flowrates through the inhalation device. The predetermined relationships maybe represented by a look-up table.

The acoustic power may be detected within a predetermined frequencyband.

One or more flow rates of the flow profile determined based on thedetected acoustic power are calibrated with respect to one or more flowrates determined based on the detected peak frequencies. Thus, it ispossible to determine, or detect, a flow rate based on the detectedacoustic power, which is subsequently calibrated or adjusted accordingto a flow rate which has been determined, or detected according to adetected peak frequency.

According to a third aspect of the invention there is provided acomputer program product having instructions stored thereon which whenexecuted on a processor performs the above-described methods.

According to a fourth aspect of the invention there is provided a methodof monitoring use of an inhalation device, comprising the steps of:instructing a user to inhale air through an inhalation device;performing any one of the above-described methods as the user inhalesair through the inhalation device; and storing the flow profile.

According to a fifth aspect of the invention there is provided a methodof training use of an inhalation device, comprising the steps of:instructing a user to inhale air through an inhalation device;performing any one of the above-described methods as the user inhalesair through the inhalation device; displaying the flow profile;determining any portions of the flow profile that require improvement;and communicating any improvements to the user.

According to a sixth aspect of the invention there is provided a devicecomprising: a processor in communication with a microphone, wherein themicrophone is configured to detect acoustic emissions; the processor isconfigured to: detect two or more peak frequencies in the measuredacoustic emissions; and generate a flow profile based on the detectedpeak frequencies.

According to a seventh aspect of the invention there is provided adevice comprising: a processor in communication with a microphone,wherein the microphone is configured to detect acoustic emissions; theprocessor is configured to: detect one or more peak frequencies in themeasured acoustic emissions; detect acoustic power of the measuredacoustic emissions; and generate a flow profile based on the detectedacoustic power and the detected peak frequencies.

The device may comprise a microphone, and may form part of a mobiledevice, such as a mobile handset or telephone. Moreover, the microphonemay be integrated within the device.

The applicants have identified that the internal swirl motion and rapidrotation of air travelling through chambers of an inhaler used toadminister a medicament causes the generation of an associated spectralpeak. This swirl motion of air causes an acoustic emission which may bereferred to as a swirl tone. In this regard, FIG. 1 is a graph whichillustrates the relationship between the spectral peak of the swirl toneand the air flow rate through a powder type inhaler. It will beappreciated that the method described herein may be applied to any formof inhalation device, and more specifically to an inhalation device thatutilises the movement of inhaled air, or an air flow, to administer amedicament to a user. More specifically the method may be applied to apower-type inhalation device that includes various passageways throughwhich air passes when inhaled. The graph in FIG. 1 illustrates themeasured frequency of the spectral peak against a known flow rate whichwas applied to the inhalers. Four inhalers were tested, and the graphillustrates the results from these four different inhalers of the sametype, and shows that the spectral peak measurement is consistent overthe range of 10 to 25 litres per minute (approximately 0.000167 to0.000417 m³/s). This is advantageous because frequency is typically easyto measure and is believed not to depend on the losses in the acousticpropagation path from the inhaler to a microphone, and the internalconversion and translation processes. Moreover, it is possible toestimate simultaneously the acoustic power in a defined bandwidth. Forexample, FIG. 2 shows a graph of acoustic power versus flow rate of thefour inhalers used to obtain the spectral peak frequencies. A band passfilter is used to filter the received acoustic emission signal from amicrophone, and the filtered signal is normalised to 0 dB audio power at20 litres per minute (approximately 0.0003 m³/s). The band pass filterused is centred at 5 kHz and has a pass band of 8 kHz.

If it is assumed that at some stage in an inhalatory flow profile theflow rate will be within the flow range of 10 to 25 litres per minute,it is possible to utilize the spectral peaks to accurately determine aflow rate measurement, independent of the acoustic power, and tocalibrate the power level of the acoustic power so that a flow profileoutside of the flow range of 10 to 25 litres per minute may be obtained.Moreover, if an accumulation time for the acoustic filtering is set to asufficiently low value (e.g., 80 milliseconds), there is a highprobability that multiple spectral peaks will be detected.

FIG. 3 shows a mobile device 10 according to an aspect of the invention.The mobile device 10 is preferably a mobile phone or handset, which maybe referred to as a smartphone. The device 10 is illustrated in thefigure as being proximal to an inhaler device 12. In the figure, thedevice 10 is within 0.1 m of the inhaler 12, but it will be appreciatedthat the device 10 and the inhaler 12 may be in contact with one anotheror may be spaced apart by up to 1 m. However, the distance between thedevice 10 and the inhaler 12 will depend on the sensitivity of atransducer (e.g., microphone) within the device 10.

FIG. 4 illustrates the mobile device 10 schematically. The device 10comprises a processor 14 coupled to a display 16, memory (e.g., RAMand/or ROM) 18, a wireless communication system 20, an input/outputinterface 22 and a transducer 24. The processor 14 is capable oflaunching and running software programs (e.g., applications) stored inthe memory 18 of the device 10. The processor 14 may receive data inputfrom various sources, such as a touch-sensitive overlay on the display16 for receiving user input, and/or the transducer 24. The transducer 24in this example is a microphone and is the microphone that is typicallyused in the mobile device 10 when a user makes and receives voice calls.The wireless communication system 20 is a short-range communicationsystem and may include a wireless bus protocol compliant communicationmechanism such as a Bluetooth® communication module to provide forcommunication with similarly-enabled systems and devices or IEEE 802.11radio standards, which is more typically known as WiFi. The wirelesscommunication system also enables the device to communicate with awireless network to provide data and voice capabilities as is well knownin the art. The memory 18 data stored thereon may be used by theprocessor 14, and the processor 14 may store data on the memory 18, suchas the results from an analysis or raw data received from an inputdevice, for example. It will be appreciated that if device 10 is asmartphone it will include various other hardware and softwarecomponents as will be known to the person skilled in the art, but whichare not described herein for simplicity.

A method for generating a flow profile using the spectral peak of aswirl tone in an inhaler is now described in association with FIGS. 3,4, and 5. The method involves calibrating the inhaler device 12 usingthe mobile device 10 to characterise the audio properties of the inhalerdevice 12. This initial calibration is performed once on a test device,such that the resultant curves, expression, look-up table and/or graphscan be used with other production inhaler devices which have beenmanufactured according to similar processes. The initial calibrationwill be described in association with the mobile device 10 using anapplication available on the mobile device 10. However, it will beappreciated that this initial calibration may be performed on a generalpurpose computer.

In the initial calibration, the inhaler 12 is coupled to a suction pump(not shown) to provide a controllable air flow through the inhaler 12 tosimulate it during normal use. The air flow through the inhaler device12 is varied from 0 to 60 litres per minute (approximately 0.001 m³/s),with 5 litres per minute increments (approximately 0.00008 m³/s). Whileair flow through the inhaler device 12 is provided by the suction pump,the microphone 24 is used to detect the acoustic emission (or acousticsound emission) produced by the inhaler 12, which is sampled by theprocessor 14 and stored in the memory 18. It will be appreciated thatthe application running on the mobile device 10 may prompt the user tobegin the air flow and to terminate the sampling by the processor 14once the air flow has been increased to its maximum value for thepurpose of the calibration. The processor 14 optionally averages thepower spectrum using known techniques.

For each flow rate (i.e., 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55 and60 litres per minute), the acoustic power is estimated by the processor14 in a spectral width of 8 kHz at a centre frequency of 5 kHz (i.e.,the sampled data for each flow rate is filtered using a band passfilter). It will be appreciated that the amplitude of the signalmeasured by the microphone can be converted to an acoustic power usingknown techniques and the properties of the microphone. The processor 14subsequently performs regression on the acoustic power measurements toobtain an expression of power in dB against flow rate. The processor 14may optionally cause the acoustic power measurements against flow rateto be displayed on the display 16, for example. The processor 14 mayalso store the obtained acoustic power measurements in a look-up tableand subsequently use linear interpolation, if required, based on thedata in the look-up table. FIG. 5 illustrates a calibration curve of theaudio power against flow rate for the inhaler device 12.

The processor 14 subsequently detects spectral peaks in the acousticsound emission at each of the induced flow rates in the range of 0 to 25litres per minute (i.e., 5, 10, 15, 20, 25 litres per minute), which maybe referred to as the low flow rates. As mentioned above, it was foundthat for a particular type of inhalation device spectral peaks wereobserved over a range of 10 to 25 litres per minute (approximately0.000167 to 0.000417 m³/s). However, it will be appreciated thatspectral peaks may be observed at higher or lower flow rates than these.Moreover, it is understood that the spectral peaks are possibly a resultof the internal swirl motion and rapid rotation of air travellingthrough chambers of an inhalation device. However, this may not be thecase for all inhalation devices, such that other inhalation devices mayexhibit spectral peaks that are not caused by the internal swirl motionand rapid rotation of air travelling through its chambers.

The spectral peak detection is obtained by a 2-dimensional backgroundestimate using a median filter and thresholding the signal sampled bythe processor 14 to identify the swirl feature when the signal exceedsthe threshold by a set amount in decibels. In particular, a Fast FourierTransform (FFT) in time is applied to the sampled signal to obtain aspectrogram. A median filter is then applied to columns of thespectrogram using a sliding window of typically 29 samples to estimate arobust background average at each time sample and frequency point. Anysignal points that are greater than a certain threshold value indecibels (e.g., 20 dB) above the local median value at that point aredesignated to be above the threshold. The peak frequency is then takento be the largest of the points which are greater than the threshold ina contiguous range of points over the threshold.

During the calibration stage, the flow rate is kept at a constant by thesuction pump, so it is typical that only a single peak frequency will bedetected. It will be appreciated that other image processing techniquesmay be used to identify and estimate the spectral peak of the swirl toneusing 2-dimensional image processing line finding or other featureextraction methods, or by Kalman filtering to track the evolution of thespectral peak in time. Once the processor 14 has obtained the spectralpeak frequency at each of the low flow rates, regression is used toobtain an expression of spectral frequency against flow rate. Theprocessor 14 may optionally display the spectral power measurementsagainst flow rate. The processor 14 may also store the obtained spectralpower measurements in a look-up table and subsequently use linearinterpolation, if required, based on the data in the look-up table.

The initial calibration of the inhaler 12 is completed by storing thedata related to the audio power and spectral frequency, and theirrespective flow rates in memory as look-up tables or mathematicalexpressions, which allows values of audio power or spectral frequency tobe input and values of flow rate to be output.

The method for obtaining a flow profile for the inhaler 12 in use is nowdescribed with reference to FIGS. 6 and 7.

The mobile device 10 is placed proximate the inhaler device 12 (e.g.,approximately 0.5 m apart). The user is asked to use the inhaler 12 inthe usual manner by drawing air through the inhaler device 12. While theuser draws air through the device, the processor 14 of the device 10detects and samples the acoustic sound emission produced by the inhaler12, which is stored in the memory 18. The processor 14 optionallyaverages the power spectrum using known techniques.

FIG. 6 (upper graph) is a time series trace of the amplitude of thesignal measured using the microphone against time as a user draws airthrough the inhaler device 12 in the usual manner over a time of 6seconds. In the upper graph of FIG. 6, the y-axis is the signalamplitude in arbitrary units when sampled by the processor 14 and isrepresentative of a constant multiplied by the microphone voltage. Thelower graph in FIG. 6 is a spectrogram that has been obtained from thetime series trace illustrated in the upper graph of FIG. 6 using thetechniques described above (i.e., FFT in time). The swirl features areillustrated in the lower graph of FIG. 6. In the lower graph of FIG. 6,the y-axis is time during the recording of the inhalation from 0 to 5seconds at sample periods of 2.67 ms, and the x-axis is frequency from 0to 48 kHz at sample periods of 187.5 Hz.

The processor 14 subsequently estimates the acoustic power within a passband having a spectral width of 8 kHz at a centre frequency of 5 kHz.The filtered signal is subsequently sampled over 80 ms blocks with a 50%overlap to obtain a 25 Hz update rate. The processor 14 subsequentlydetects the spectral frequency (i.e., the spectral peaks) of the swirltones of the signal at 25 Hz intervals and converts these to flow ratesusing the predetermined expression or look-up table for flow rates. Itwill be appreciated that in this example flow rates of less than 25litres per minute (i.e., the low flow rates) are determined using thespectral peaks. The spectral peaks are estimated using the medianfiltering and thresholding, as is described above for the calibrationprocess. This is to say that the largest spectral peak in the range offrequencies, for example, 5 kHz to 20 kHz is identified. It will beappreciated that it may not be possible to identify a spectral peak in asampled time period, but if this is the case, it should be possible toidentify at least one spectral peak over the extent of the times seriesdata.

The processor 14 subsequently uses the expression or look-up table ofacoustic power values to convert the detected acoustic power to flowrates. The flow rates obtained using the acoustic power measurements aresubsequently adjusted, or calibrated, as appropriate using the flowrates obtained using the spectral frequency of the swirl tones. Forexample, the processor 14 determines the flow rate for a specifiedsample obtained at selected time. The acoustic power at the sameselected time and its associated flow rate is obtained from the look-uptable of acoustic power values. If the acoustic power flow rate does notequal the spectral peak flow rates, within a predetermined tolerance(e.g., 5%), an adjustment factor for the acoustic power flow rate isdetermined, and is applied to all of the previously converted acousticpower flow rates. The adjustment may involve addition, subtraction,multiplication or division or any combination thereof. The adjustmentvalue is typically an acoustic power value in dB such that it issubtracted or added to the acoustic power values. This process may berepeated for all of the detected spectral peak flow rates, and theadjustment factor obtained for each spectral peak flow rate may becombined. Once the acoustic power flow rates have been adjusted (i.e.,calibrated), a report of flow rate against time can be generated in theform of a graph for example. This is referred to as a flow profile.

In the example described above, it is assumed that only a singlespectral peak is detected when the method described herein is used toproduce a flow profile. However, it is possible that multiple spectralpeaks may be detected. If multiple spectral speaks are detected (i.e.,multiple time periods within the sample data from the microphone aredetermined to include a spectral peak) the (linear) implied powers foreach of the spectral peaks are summed and the corresponding measuredaudio powers are summed and a ratio is taken therefrom. The acquiredratio is subsequently converted to decibels to give the calibrationoffset. The implied power is determined by estimating the flow thatcorresponds to the swirl frequency peak, and then estimating the audiopower based on the audio power versus flow rate data/look-up from thecalibration stage. It will be appreciated that the same technique isused if a single spectral peak is detected, but it will not be necessaryto sum any values.

FIG. 8 is a flow chart 30 depicting a method performed by the processor14 of the mobile device 10, which is now described in association withFIG. 7. FIG. 7 graphically illustrates the method shown in the flowchart of FIG. 8. The steps may be performed in a different order thanillustrated, and one or more steps may be optional.

At block 32, the device 10 detects and samples the acoustic soundemission produced by the inhaler 12, whilst a user draws air through theinhaler 12.

At block 34, the device 10 estimates the acoustic power using a spectralwidth of 8 kHz at a centre frequency of 5 kHz. This is illustrated inFIG. 7 as line 50. The device 10 may optionally average the powerspectrum for each sample point.

At block 36, the device 10 samples the filter signal over 80 ms blockswith a 50% overlap to obtain a 25 Hz update rate. This is illustrated inFIG. 7 as line 52.

At block 38, the device 10 detects the spectral frequency of the swirltones (see FIG. 7, crosses 54) and converts these to flow rates usingthe predetermined expression or look-up table for flow rates less than25 litres per minute, for example (i.e., the low flow rates). Theconverted flow rates obtained from the spectral frequency of the swirltones are illustrated in FIG. 7 as crosses 56.

At block 40, the device 10 converts the detected acoustic power to flowrates using the expression or look-up table of acoustic power values.This is illustrated in FIG. 7 as line 58.

At block 42, the device 10 calibrates the flow rates obtained using theacoustic power measurements according to the flow rates obtained usingthe spectral frequency of the swirl tones.

At block 44, the device 10 generates and outputs a flow profile of flowrate against time. This is illustrated in FIG. 7 as line 60.

Thus, the method described herein simplifies the calibration process,whilst retaining the ability to make accurate measurements. Moreover,any modification to the inhaler is reduced or eliminated.

In the embodiment described above, all of the processing including theinitial calibration is performed on a single mobile device. However, itwill be appreciated that the mobile device 12 may be used only to samplethe acoustic sound emission from the inhaler 12, which is subsequentlytransmitted to a general purpose computer, for example using WiFi,whereby the processing is performed by the general purpose computer. Themobile device 10 may receive the flow profile data for display on itsdisplay 16. The general purpose computer may be at the same location asthe mobile device 10 user, or may be remotely located elsewhere, forexample. Moreover, a discrete microphone connected to a general purposecomputer or the mobile device 10 may be used to sample the acousticsound emission from the inhaler 12, and the microphone may be optionallyfixed to the inhaler 12 using a mechanical fixing or constraint, or asuitable adhesive. If using a microphone fixed to the inhaler 12, it maybe a wireless enabled (e.g., WiFi or Bluetooth®) or wired microphone toenable it to communicate with the processing device.

FIG. 9 illustrates a series of graphs which may be obtained when themethod described above is performed using a smartphone and anapplication running thereon to sample the acoustic sound emissionsproduced by the inhaler 12 during normal use. The sampled data wassubsequently transmitted to a general purpose computer for processing.The upper graph represents the data received from the smartphone afterit has been filtered and sampled. In the upper graph, the solid line 62is the audio power and the crosses 64 are the detected spectral peaks.The central graph represents the flow rates obtained from the spectralpeaks (crosses 66) and the flow rates obtained from the acoustic powerand converted/calibrated using the spectral peaks (solid line 68).Finally, the lower graph is the reported flow profile (solid line 70).

The method of generating a flow profile of the inhalation device may beused to monitor the use of an inhalation device, for example. In thisregard, a user is instructed to inhale air through an inhalation deviceand a flow profile is generated, as is discussed above. The flow profileis then stored and or transmitted elsewhere for assessment or comparisonwith previous/future flow profiles or a preferred (i.e., “ideal”) flowprofile. Moreover, a user may be trained to use an inhalation devicebased on a generated flow profile. For example, a user is instructed toinhale air through an inhalation device and a flow profile is generated.A practitioner subsequently displays the flow profile and determines anyportions or sections of the flow profile that could be improved andcommunicates these to the user. It will be appreciated that this form oftraining or monitoring could be used by a practitioner remotely locatedwith respect to the user.

The examples described herein refer to specific ranges and values.However, it will be apparent to the skilled person that these are onlyexamples and should not be considered to limit the invention. Forexample, the inhaler device has been calibrated herein with a flow rateof up to 60 litres per minute (approximately 0.001 m³/s), but it will beappreciated that the calibration may be performed with greater flowrates of up to 200 litres per minute (approximately 0.0033 m³/s), forexample, and specifically 120 litres per minute (approximately 0.002m³/s). These calibrated values can then be used to produce a flowprofile with greater flow rates.

The embodiments described in accordance with the present invention maybe provided as a computer software product. The computer softwareproduct may be provided in, on or supported by a computer readablemedium which could be provided as all possible permanent andnon-permanent forms of computer readable medium either transitory innature, such as in a data transmission signal for example sent over theinternet, or non-transitory in nature such as in the memory 18 of thedevice 10 or other, non-volatile storage such as memory. On the otherhand the computer readable medium may be a non-transitory computerreadable medium comprising all computer-readable media.

The term “computer readable medium” (or non-transitory computer readablemedium) as used herein means any medium which can store instructions foruse by or execution by a computer or other computing device including,but not limited to, a portable computer diskette, a hard disk drive(HDD), a random access memory (RAM), a read-only memory (ROM), anerasable programmable-read-only memory (EPROM) or flash memory, anoptical disc such as a Compact Disc (CD), Digital Versatile Disc (DVD)or Blu-ray™ Disc, and a solid state storage device (e.g., NAND flash orsynchronous dynamic RAM (SDRAM)).

It will be appreciated that the foregoing discussion relates toparticular embodiments. However, in other embodiments, various aspectsand examples may be combined.

1-20. (canceled)
 21. A method for detecting acoustic emissions within aninhaler device having at least one chamber through which air may passupon inhalation by a user of the inhaler, the method comprising thesteps of: positioning an acoustic sensor and an inhaler device intospaced-apart proximity with each other, wherein said acoustic sensor isnot physically coupled to the inhaler, and wherein the acoustic sensoris in electrical communication with a processor; and measuring acousticemissions induced by a user generating an inhalation flow movementthrough the inhaler device; and generating a signal indicative of saidmovement.
 22. The method of claim 21 wherein the signal indicative ofsaid movement comprises a flow profile.
 23. The method of claim 22wherein the inhalation flow movement comprises a rotational flow. 24.The method of claim 23 wherein the flow profile comprises adherencemonitoring.
 25. The method of claim 21 wherein the acoustic sensor andinhaler are spaced apart by a distance of at least 0.1 meter.
 26. Themethod of claim 25 wherein the acoustic sensor and inhaler are spacedapart by a distance of up to 1 meter.
 27. The method of claim 21 whereinthe acoustic sensor comprises a microphone.
 28. The method of claim 27wherein the microphone and processor are part of a mobile device. 29.The method of claim 28 wherein the mobile device comprises a smartphone.
 30. The method of claim 28 wherein the mobile device comprises acomputer.
 31. A method of training a patient in the correct use of aninhaler, the method comprising, providing an inhaler device having atleast one chamber through which air may pass upon inhalation by apatient user of the inhaler; instructing the patient to configure theinhaler for medicament delivery; instructing the patient to position,within 1 meter of the inhaler, a mobile device comprising an acousticsensor, signal processing software and a processor in electricalcommunication with the acoustic sensor, and inhale the medicament;measuring acoustic emissions induced by a user generating an inhalationflow movement through the inhaler device; and generating a signalindicative of said movement; determining any portion of the flow profilethat requires improvement; and communicating said improvement to thepatient.
 32. A kit comprising an inhaler and instructions for use,wherein the instructions for use comprise instructing a patient to:configure the inhaler for medicament delivery to the patient; positionan acoustic sensor within 1 meter of the inhaler device, the acousticsensor being in electrical communication with a processor and withsignal processing software; and inhale the medicament; and wherein themobile device measures acoustic emissions induced by the patient togenerate an inhalation flow movement through the inhaler device; and togenerate a signal indicative of said movement.
 33. The kit of claim 32wherein the signal indicative of said movement comprises a flow profile.34. The kit of claim 33 wherein the flow profile comprises adherencemonitoring.